We present a collection of publicly available intrinsic aqueous solubility data of 829 drug‐
like compounds. Four different machine learning algorithms (random forests [RF], LightGBM …

In this work, a dataset of more than 200 nitroaromatic compounds is used to develop
Quantitative Structure–Activity Relationship (QSAR) models for the estimation of in vivo …

In this study, we developed machine learning-based prediction models for early childhood
caries and compared their performances with the traditional regression model. We analyzed …

Drug-induced liver toxicity is one of the significant safety challenges for the patient's health
and the pharmaceutical industry. It causes termination of drug candidates in clinical trials …

With the development and application of nanomaterials, their impact on the environment and
organisms has attracted attention. As a common nanomaterial, nano-titanium dioxide (nano …

Methods for dimensionality reduction are showing significant contributions to knowledge
generation in high-dimensional modeling scenarios throughout many disciplines. By …

The inhibitors of two isoforms of mitogen-activated protein kinase-interacting kinases (ie,
MNK-1 and MNK-2) are implicated in the treatment of a number of diseases including …

The emergence of multidrug-resistant (MDR) strains with perturbed metabolic networks
(MNs) pushes researchers to improve antibacterial drugs (ADs). Certain nanoparticles (NPs) …

Effective computational prediction of complex or novel molecule syntheses can greatly help
organic and medicinal chemistry. Retrosynthetic analysis is a method employed by chemists …

Maternal nutrition and lifestyle in pregnancy are important modifiable factors for both
maternal and offspring's health. Although the Mediterranean diet has beneficial effects on …